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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM29415
Volume:
8 |
3 |
Mar 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
People will believe in what they see rather than hidden facts. In recent times as technology is improving and it became very easy to change a particular person in an existing image or video with someone else. So, spreading these types of modified videos causes spamming and peculating wrong information over social media and this will cause the great extent of misleading and threatening to the common people. To overcome these tedious situations, we are building a deep learning model that will identify the genuinity of the video or image in terms of the origin of its source. In our proposed system we are using Long Short-Term Memory and ResNext.
KEYWORDS
Publication Date
12/31/45368
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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